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Hill 型肌肉模型的数值不稳定性。

Numerical instability of Hill-type muscle models.

机构信息

School of Sport, Exercise & Rehabilitation Sciences, University of Birmingham, Birmingham, UK.

Cardiff School of Sport and Health Sciences, Cardiff Metropolitan University, Cardiff, UK.

出版信息

J R Soc Interface. 2023 Feb;20(199):20220430. doi: 10.1098/rsif.2022.0430. Epub 2023 Feb 1.

Abstract

Hill-type muscle models are highly preferred as phenomenological models for musculoskeletal simulation studies despite their introduction almost a century ago. The use of simple Hill-type models in simulations, instead of more recent cross-bridge models, is well justified since computationally 'light-weight'-although less accurate-Hill-type models have great value for large-scale simulations. However, this article aims to invite discussion on numerical instability issues of Hill-type muscle models in simulation studies, which can lead to computational failures and, therefore, cannot be simply dismissed as an inevitable but acceptable consequence of simplification. We will first revisit the basic premises and assumptions on the force-length and force-velocity relationships that Hill-type models are based upon, and their often overlooked but major theoretical limitations. We will then use several simple conceptual simulation studies to discuss how these numerical instability issues can manifest as practical computational problems. Lastly, we will review how such numerical instability issues are dealt with, mostly in an ad hoc fashion, in two main areas of application: musculoskeletal biomechanics and computer animation.

摘要

Hill 型肌肉模型是肌肉骨骼仿真研究中非常受欢迎的唯象模型,尽管它们是在近一个世纪前提出的。在仿真中使用简单的 Hill 型模型而不是更新的横桥模型是有充分理由的,因为计算上“轻量级”——尽管不太准确——的 Hill 型模型对于大规模仿真具有很大的价值。然而,本文旨在邀请人们讨论仿真研究中 Hill 型肌肉模型的数值不稳定性问题,这些问题可能导致计算失败,因此不能简单地将其视为简化的不可避免但可接受的后果。我们将首先重新审视 Hill 型模型所基于的力-长度和力-速度关系的基本前提和假设,以及它们经常被忽视但却是主要的理论局限性。然后,我们将使用几个简单的概念性仿真研究来讨论这些数值不稳定性问题如何表现为实际的计算问题。最后,我们将回顾在两个主要应用领域中,即肌肉骨骼生物力学和计算机动画,如何处理这些数值不稳定性问题,这些问题大多是以特定方式处理的。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6912/9890125/d0dcf0f5bf7d/rsif20220430f01.jpg

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